tbuckley/cabot-search huggingface dataset:
Abstract 11315: Clinical Utility of Machine Learning-Derived Vocal-Biomarker in the Management of Heart Failure
Authors: Kozo Okada, Yasuhiro Omiya, Daisuke Mizuguchi, Koji Endo, Yusuke Kobayashi, yasushi matsuzawa, Noriaki Iwahashi, Masami Kosuge, Toshiaki Ebina, Kouichi Tamura, Kiyoshi Hibi
Journal: Circulation (2022)

Introduction: Previous studies have suggested that early therapeutic intervention could prevent heart failure (HF) worsening, while early detection of signs and symptoms of cardiac decompensation remains challenging. For the first time, this study focused on voice symptoms and aimed to explore its potential utility in the management of heart failure. Methods: This single-center, prospective, observational study included 38 patients admitted due to worsening HF. A total of 726 voice data were recorded during the therapeutic time course at the hospital. Changes in clinical symptoms (New York Heart Association [NYHA])) evaluated by an experienced cardiologist and B-type natriuretic peptide (BNP, pg/ml) during the time course were also evaluated. Here we tested if the acoustic features of the patient voice could predict the NYHA class and BNP levels, using the machine learning (ML) models trained with a gradient boosting algorithm. A 5-fold cross-validation was applied to evaluate the model performance. Results: There were significant correlations of some acoustic features with clinical symptoms and BNP levels (data not shown). We created the prototype of the ML model on the acoustic features extracted from the data set. Receiver operating characteristic (ROC) analysis revealed a good diagnostic accuracy of our ML model to predict NYHA class ≥2 (sensitivity 0.78, specificity 0.75, area under the curve (AUC) 0.79, and accuracy 0.77). There was also a significant correlation between voice-derived BNP and actual BNP levels (Figure). AUC of ROC analysis for predicting NYHA class ≥2 from BNP was 0.688. Conclusions: The prototype of the ML model was related to clinical symptoms of HF decompensation and BNP levels, demonstrating greater diagnostic accuracy for NYHA prediction than actual BNP levels. Further studies are warranted to investigate the possible contributions of our ML model to the early detection of worsening HF as ML-derived vocal-biomarkers.
Abstract 13798: Obstructive Sleep Apnea Severity and Abnormal Right Ventricular Flow Reserve in Adult OSA Patients Who Received Rubidium-82 Cardiac PET Perfusion Imaging
Authors: Ehimen C Aneni, Edward J Miller, Gul Jana Saeed, Robert deKemp, RAN KLEIN, Rob S Beanlands, Henry K Yaggi, Albert J Sinusas, Stephanie Thorn
Journal: Circulation (2022)

Background: Obstructive sleep apnea (OSA) is associated with right ventricular (RV) remodeling, RV dysfunction and pulmonary hypertension. Myocardial flow reserve (MFR), the ratio of stress-to-rest myocardial blood flow (MBF), is an index of coronary microvascular health. Recent evidence suggests that severe OSA is associated with abnormal left ventricular MFR (LVFR). However, little is known about MFR in the RV of patients with OSA. In this study we examined the relationship between measures of OSA severity and RV MFR (RVFR) in humans. Methods: We conducted RV MBF assessment in 47 persons with OSA who had a cardiac positron emission tomographic (PET) perfusion scan. All participants had in-laboratory polysomnography. RVFR &lt;2.0 was chosen as threshold for abnormal RVFR to coincide with the 25 th percentile of RVFR in our sample. Abnormal LVFR was also defined as &lt;2.0 based on thresholds from previously determined studies. We compared the mean apnea-hypopnea index (AHI), oxygen desaturation index (ODI) and time spent with &lt;90% oxygen saturation (T90%). Results: The mean age of the participants was 58 years and 63% were female. There was a strong correlation between RVFR and LVFR (Spearman Rho = 0.63, P&lt;0.001). The mean AHI was greater among persons with RVFR &lt;2 compared to those with RVFR≥2 [mean (SE) AHI: 63 (20) v. 32 (5), P=0.042]. This trend was observed with the ODI although it was not statistically significant. Given the RVFR and LVFR were strongly correlated, we created a ratio of RVFR to LVFR to account for the LV MBF. The mean AHI and ODI among persons with RVFR/LVFR &lt;1 was greater than those with ≥1; p = 0.025 and p=0.031 respectively. See the figure for more details. Conclusion In patients with OSA, patients with reduced RVFR had higher AHI and ODI indicating greater severity of OSA. The exact mechanism behind this phenomenon is not known. Future studies should further characterize the relationship between RV myocardial blood flow and OSA.
Abstract 14265: Proteomic Discovery of Molecular Pathways in Patients With Biopsy-Proven Myocarditis
Authors: Eui-Soon Kim, Donggi Jang, Yeonju Kyoung, Jeesoo Kim, Seonhwa Lee, In-cheol Kim, Jong-Seo Kim, Jong-Chan Youn
Journal: Circulation (2022)

Introduction: Myocarditis is an inflammatory disease of the myocardium that results in injury to the cardiac myocytes. However, there is a lack of research focusing on its immune reaction. Also, most studies have been done through analysis of peripheral blood. Here, we aimed to identify proteome-based immunopathogenesis in patients with biopsy-proven myocarditis. Methods: Comparative proteomic analysis of right ventricle biopsy specimens was performed from six patients with myocarditis and four controls (normal endomyocardial biopsy specimens from one-year surveillance of heart transplant recipients) by tandem mass tag combined with liquid chromatography-mass spectrometry. Based on the results of protein expression, cell fractions were calculated using CIBERSORTx and Gene ontology (GO), and ingenuity pathway analysis was conducted to address immune features and related molecular mechanisms in myocarditis. Results: In total, 720 up-regulated proteins were screened. The top 10 GO terms in up-regulated proteins were mostly related to immune response. Also, the T follicular helper (Tfh) cells and plasma cell fractions were significantly increased in myocarditis. The ingenuity pathways analysis showed that the pathway for activation and immune response of immune cells included signaling of interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α) with other mediators including interferon regulatory factor (IRF) 1,5, 7 and signal transducer and activator of transcription 1 (STAT1). Conclusions: From mass spectrometry protein analysis, we revealed that Tfh cells and plasma cells play a major role in the development of immune response in myocarditis. Also, TNF-driven interferon response via STAT1 and IRFs can be the main pathways for B cell activation by Tfh cells. Further studies are necessary to validate whether these proteins correlate with the clinical characteristics or can be used as biomarkers for myocarditis.
Abstract 12284: Utilizing Automated Machine Learning for Rheumatic Heart Disease Detection in Doppler Echocardiography
Authors: Kelsey Brown, Pooneh Roshanitabrizi, Andrea Z Beaton, Emmy Okello, Joselyn Rwebembera, Marius Linguraru, Craig A Sable
Journal: Circulation (2022)

Introduction: Rheumatic heart disease (RHD) is the number one cause globally of morbidity and mortality from heart disease in children and young adults. The mitral regurgitation (MR) jet length on color Doppler echocardiography is an important index for diagnosis, but its measurement and interpretation vary. Objective: Develop an automatic machine learning approach to identify and measure the MR jet length on color Doppler for RHD detection. Methods: We used 316 echocardiograms from 95 children (mean age 12±2 years; range 5 to 17 years) with DICOM color Doppler images of the mitral valve taken from parasternal long axis (PLAX) and apical 4 chamber (AP4) views. All echocardiograms were independently reviewed by an adjudication panel consisting of four expert pediatric cardiologists to determine maximum MR jet length and diagnosis (RHD or normal). Among 95 cases, 29 were normal and 66 had RHD. Our automated method included. (1) Selection of frames during ventricular systole using a convolutional neural network architecture. (2) Localization of left atrium using convolutional neural networks with LinkNet structure. (3) Measurement of MR jet length by image color analysis. (4) Detection of RHD by applying a generalized regression model based on the maximum MR jet length measured and maximizing the balanced accuracy using cross validation. Results: Machine learning selected the correct systolic frame with an average accuracy of 0.95 (sensitivity 97%/specificity 93%) and 0.94 (sensitivity 94%/specificity 94%) for the AP4 and PLAX view, respectively. It localized the atrium with an average Dice coefficient of 0.89 and 0.9 for the AP4 and PLAX view, respectively. We estimated the MR jet length with an average absolute error of 0.33±0.4 cm (p-value = 0.15 compared to manual measurements). Our deep learning approach performed similar to or better than previously published manual methods for categorization of RHD positive vs negative. The accuracy of RHD detection was 0.84 (sensitivity 86%/specificity 79%). Conclusions: Our automatic method has the potential to reliably detect RHD as accurately as expert cardiologists. This innovative approach holds promise to scale echocardiography screening for RHD and expand prophylaxis to prevent progression of RHD globally.
Abstract 14377: Alteration in Cardiac Function via Upregulation of Interferon Pathway in Skeletal Muscle
Authors: Manju Kumari, Ioannis Evangelakos, Norbert Frey, Joerg Heeren
Journal: Circulation (2022)

Introduction: Cardiac abnormalities are a major cause of death in patients with myositis. Chronic inflammation resulting from increased infiltration of inflammatory cells in skeletal muscle followed by muscle weakness and myofiber atrophy is a characteristic of myositis. Transcriptomics and myopathological studies show IFN-1 pathway play a major role in pathophysiology of myositis. However, we do not understand how does IFN-1 signaling from inflamed skeletal muscle regulates cardiac function. Interferon regulatory factor 3 (IRF3) is a key transcriptional regulator of IFN-1 signaling cascade. Here we generated a skeletal muscle-specific IRF3 transgenic mouse model that recapitulates muscle atrophy and cardiac dysfunction facilitated by tissue cross-talk via elevated IFN-1 levels. Hypothesis: Persistent inflamed microenvironment by IRF3 and IFN-1 levels in skeletal muscle impairs muscle fitness, alters metabolome as well as myokine signaling and generates cardiac stress followed by impaired cardiac metabolism. Methods: Skeletal muscle-specific transgenic mouse model with constitutive activation of IRF3 was exploited to mimic sustained IFN-1 signaling found in myositis in vivo. Effect on muscle inflammation and weakness was determined by gene expression analysis and forelimb grip strength. Effect on cardiac inflammation, mitochondrial function, and heart function was examined. Histological assessment was done to determine fiber cross-sectional area and fiber type in whole muscle and myocytes. Results: Our data show increased mRNA levels of IRF3 in muscle atrophy model. Characterization of skeletal muscle-specific IRF3 transgenic mice showed activation of genes regulating IFN-1 pathway ( Isg15 , Ifit1 , Rsad2 , and Mx2 , etc.) and macrophage infiltration ( CD14 , CD68 ) in skeletal as well as cardiac muscle. In vitro and in vivo histological analysis showed alteration in fiber type markers. The inflammatory milieu generated by IRF3 altered metabolome and myokine levels affecting transcriptional molecular circuits regulating tissue cross-talk and metabolic pathways in the heart. Conclusion: Our studies identified skeletal muscle-specific activation of IRF3 as a model to study IFN-1 induced damage to cardiac function in vivo.
Abstract 12196: Effect of Metformin on Heart Failure in Patients With Diabetes Mellitus Receiving Anthracycline Chemotherapy
Authors: Takeshi Onoue, Yu Kang, Bénédicte Lefebvre, Amanda M Smith, Srinivas Denduluri, Marielle Scherrer-Crosbie
Journal: Circulation (2022)

Introduction: The prevention of heart failure (HF) is an essential issue in patients treated with anthracyclines, however, existing treatments have demonstrated modest effects. Metformin (MET), widely used to treat diabetes, protects from anthracyclines-induced cardiotoxicity in vitro and in murine models. However, there is no research investigating the cardioprotective effects of MET in patients treated with anthracyclines. Hypothesis: MET is cardioprotective in patients treated with anthracyclines. Methods: Out of 5655 patients undergoing new anthracyclines therapy at a tertiary center between 2008-2021, 260 patients were treated with MET. The clinical characteristics associated with the use of MET were identified and a propensity-score (gender, diabetes, type of cancer, kidney and cerebrovascular disease) used to match 200 patients treated with MET to 200 patients without MET. The primary outcome was new-onset symptomatic HF defined by the AHA/ACC guidelines occurring within 1 year of the initiation of anthracyclines. Proportional hazard analysis was used to identify characteristics associated with HF. Results: Patients were 65 years old [57-70], 34% male. No differences were noted in age, cardiovascular risk factors, history, use of beta-blockers and ACE inhibitors between the MET and non MET groups. Six patients (3%) treated with MET and 20 matched patients (10%) developed HF within 1 year of anthracyclines initiation (P=0.004, Figure). Use of MET ([HR]: 0.27; 95% CI: 0.1 to 0.64; p = 0.002), use of insulin (HR: 2.27; 95% CI: 1.05 to 5; p = 0.04), coronary artery disease (HR: 4.69; 95% CI: 2.06 to 10.2; p &lt; 0.001), and chronic kidney disease (HR: 2.65; 95% CI: 1.21 to 5.77 p = 0.02) were associated with incident HF. Conclusions: MET significantly reduced the risk for HF in patients treated with anthracyclines. Our findings are consistent with previous experimental studies and suggest a new therapeutic option in the prevention of cardiotoxicity.
Abstract 12956: Pulmonary Vein Thrombosis: A Rare Complication Following Infection With SARS-CoV-2
Authors: Mithun R Suresh
Journal: Circulation (2022)

Case Presentation: 49 year old male with past medical history of hypertension who presented with dyspnea and nasal congestion of three days duration. Testing for SARS-CoV-2 was positive. ECG revealed sinus tachycardia with an incomplete right bundle branch block. D-dimer was elevated 3,388 ng/mL and CT pulmonary angiogram revealed thrombosis of a right lower lobe pulmonary vein extending to the posterior aspect of the left atrium along with consolidation in the right lower lobe concerning for pulmonary infarct versus congestion in the setting of pulmonary venous thrombosis. The patient was admitted and started on intravenous unfractionated heparin. Echocardiogram performed later in the day revealed left ventricular segmental wall motion to be globally hypokinetic with mildly reduced ejection fraction of 45%. Left atrium was severely enlarged. No thrombus could be seen in the left atrium or ventricle. Bubble study revealed no evidence of atrial septal defect or patent foramen ovale. The next day after admission, his symptoms had resolved and he was back to his baseline, so he was discharged. No supplemental oxygen was required. Heparin was transitioned to apixaban, and metoprolol succinate and lisinopril were initiated. Cardiac monitoring during the hospitalization did not demonstrate any arrhythmias. Etiology of his pulmonary vein thrombosis was ultimately felt to be due to coagulopathy secondary to COVID-19 given that the patient’s medical history was otherwise unremarkable. Discussion: This case describes a rare complication due to infection with SARS-CoV-2. Pulmonary artery thrombi are common with SARS-CoV-2 infection, but pulmonary vein thrombi are rare. With thrombus extending to the left atrium, cardiac monitoring was performed and did not reveal evidence of atrial fibrillation or atrial flutter. With no other identifiable cause of the thrombus, the etiology was likely due to SARS-CoV-2 infection.
Abstract 14062: Longitudinal Rate of Change for Cardiac Magnetic Resonance Biomarkers Associates With Mortality in Duchenne Muscular Dystrophy
Authors: Jonathan H Soslow, Meng Xu, Joseph Starnes, Kristen GeorgeDurrett, Kimberly Crum, Frank J Raucci, Christopher Spurney, Kan N Hor, Linda Cripe, Nazia Husain, Katheryn E Gambetta, Sujatha Buddhe, James C Slaughter, Larry W Markham
Journal: Circulation (2022)

Introduction: Cardiomyopathy (CM) is the leading cause of death in Duchenne muscular dystrophy (DMD). Progression is variable. Multiple DMD-specific CM medications are in development, but there are no established outcome measures for therapeutic trials. Our prior work demonstrated an association between cardiac magnetic resonance (CMR) metrics and mortality, including left ventricular ejection fraction (LVEF), ventricular volumes, and native T1 mapping. The objective of this study was to determine whether longitudinal change in these metrics associates with all-cause mortality. Methods: Seventy-eight DMD subjects underwent 211 comprehensive CMR studies, including LVEF, indexed LV end diastolic and systolic volumes (LVESVi and LVEDVi), and native T1 mapping. To explore how the slope of CMR biomarkers affects mortality, multivariable linear regression was used to model age, mortality, and the interaction term of age and mortality on predictors of interest (LVEF, LVEDVi, LVESVi, native T1). Results: At baseline CMR, the median age was 12.5 years (range 7.4-27.5), and the median LVEF was 57%; 32 subjects (41%) had LVEF &lt; 55%. LGE was present in 54 subjects (71%). Fifteen subjects (19%) died over a median follow up of 5 years (IQR 3.1,7). The slope of LVEF decline differentiated between subjects with and without mortality (p&lt;0.001) ( Figure 1 ). A steeper increase in LVEDVi and LVESVi also associated with mortality (p&lt;0.001), while change in native T1 did not. Conclusions: DMD all-cause mortality is associated with the slope of progression of LVEF and ventricular volumes. Aggressive medical therapy to decrease the rate of progression may improve mortality in this patient population. In addition, a decrease in the rate of progression may serve as a valid surrogate outcome measure for therapeutic trials.
Abstract 13069: Left Atrial Mechanics in Patients With Hypertrophic Cardiomyopathy
Authors: Daniel Dalos, Christopher Mann, Theresa - Marie M Dachs, Marc Srdits, Christina Binder, Christina Kronberger, Franz Duca, Martin Huelsmann, Christian Hengstenberg, Johannes Kastner, Irene M Lang, Thomas A Zelniker
Journal: Circulation (2022)

Background: Patients with hypertrophic cardiomyopathy (HCM) frequently have diastolic dysfunction (DD) characterized by elevated filling pressures. Speckle-tracking analysis of the left atrium (LA) is an imaging tool for quantifying DD, however, its value in HCM is not well established. Methods. Transthoracic echocardiographic images of consecutive HCM patients with a septal thickness ≥15 mm and no aberrant loading conditions at an academic tertiary care center were evaluated. Peak atrial longitudinal strain (PALS) was determined by averaging the atrial strain over all segments in the 4- and 2-chamber views ( Figure ). Results. Among 205 HCM patients, 108 patients (52 years, 40% female) had sinus rhythm and sufficient image quality to be included. The median interventricular wall thickness was 20 mm (IQR 17-23), the relative wall thickness ratio was 0.65 mm (IQR 0.46-0.87), and the LV mass index was 164.0 g/m 2 (IQR 131.5-188.5). The mean PALS was 18.5% (± 8.8%) and did not differ between men and women. PALS significantly (all p &lt;0.05) correlated with septal thickness (r=-0.31), LA volume index (r=-0.60), E/A ratio (r=-0.25), E/E’ (r=-0.63), systolic pulmonary pressure (r=-0.31), and high sensitivity troponin-T levels (r=-0.43). Moreover, PALS correlated with resting gradients in patients with relevant LV outflow tract obstruction (n=53 [49%]; r=-0.29). Among patients who underwent cardiac magnetic resonance imaging (81%), PALS was significantly correlated with LA ejection fraction (r=0.59) and late gadolinium enhancement of the total LV mass (r=-0.42). In addition, PALS was the only echocardiographic parameter reflecting DD that was significantly associated with the presence of LGE (Odds Ratio 0.93, 95%CI 0.88-0.99). Conclusion. PALS is a useful tool for quantifying DD in HCM patients and is associated with the presence of LGE. Future research will need to evaluate its significance in early identification of HCM patients at risk of sudden cardiac death.
Abstract 13803: Contribution of Clinical Trial Event Data by Data Source: Insights From the ADAPTABLE Trial
Authors: Jennifer A Rymer, Hillary Mulder, Lisa M Wruck, Daniel Munoz, Sunil Kripalani, Mark B Effron, Kamal gupta, Eileen M Handberg, Sandeep Jain, Saket Girotra, Jeffrey Whittle, Rachel Hess, Catherine Benziger, Kirk U Knowlton, Lesley Curtis, Matthew T Roe, Bradley G Hammill, Russell Rothman, Josephine Harrington, Adrian F Hernandez, William Jones
Journal: Circulation (2022)

Introduction: Pragmatic randomized controlled trials (RCT) often use multiple data sources to examine clinical events, but the relative contribution of data sources (patient-reported, electronic health records (EHR), private/public claims data) to clinical endpoint rates is often not examined. Hypothesis: We hypothesized that claims data would contribute the highest number of events relative to other data sources. Methods: The ADAPTABLE study was an open-label, pragmatic RCT that demonstrated no significant difference in major cardiovascular or bleeding events among patients with CV disease randomized to an aspirin dose of 81vs. 325 mg/daily. We assessed the clinical endpoint rates and contribution of clinical endpoints by data source among patients who had EHR, public and private insurance claims data, and/or patient-reported (portal) data. Results: Of 15,076 patients randomized, there were 1,412 patients with EHR-only data; 8,756 with portal and EHR data; and 4,291 patients with portal, EHR, and claims data (Medicare or private). Patients with EHR-only data were younger (63.7 years) compared to the other groups (65.6-71.1 years); and were more likely Black (10.6%) vs. the other groups (6.3%-9.7%), p&lt;0.001. The table demonstrates trial clinical event rates by data source among patients with available portal, EHR, and claims data. Among patients with available portal, EHR, and claims data, Medicare claims data contributed the most events for the composite endpoint (77.5%) and all-cause death (97.3%), while EHR data contributed the most events for MI (74.3%), stroke (74.3%), and major bleed (73.3%). Conclusions: In a large pragmatic trial, Medicare claims data contributed the most clinical events for the primary composite outcome and all-cause death, when compared with other available data sources. Further work is needed to understand the data source combinations that most effectively provide clinical endpoint data in RCTs.